Modeling of Cementitious Representative Volume Element with Additives

Shahzamanian, M. M.; Basirun, Wan Jeffrey

doi:10.1142/s1756973717500032

Cited by 4 publications

(1 citation statement)

References 59 publications

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“…Shahzamanian et al used CEMHYD3D to simulate the representative volume element (RVE) of cementitious systems (Type I cement) containing fly ash (Class F) through a voxel-based finite element analysis (FEA) approach [21]. This research considered the effect of fly ash on the elasticity of cement properties based on the mass and volume replacements.…”

Section: Introductionmentioning

confidence: 99%

Novel hybrid HGSO optimized supervised machine learning approaches to predict the compressive strength of admixed concrete containing fly ash and micro-silica

Chen

2022

Eng. Res. Express

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Using machine learning models to provide a reliable and accurate model to predict the compressive strength of high-performance concrete helps save the time-cost and financial cost of concrete casting. On the other hand, applying admixtures such as fly ash and silica fume in the concrete structure to replace cement helps diminish carbon dioxide emissions. In the present study, a support vector machine-based regression was considered to overcome the difficulties of compressive strength, which is intensified with a modern mix design of high-performance concrete. The reliability and accuracy of the model were enhanced by providing an optimal structure by employing novel Henry's gas solubility optimization (HGSO) and particle swarm optimization (PSO) algorithms. The comparative study aimed to prove that the model optimized with Henry's gas solubility algorithm has a higher potential in predicting compressive strength. The obtained OBJ values for HGSO based model and PSO-based model of 1.4156 and 1.5419, respectively, confirmed the higher accuracy of HGSO based model.

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Section: Introductionmentioning

confidence: 99%

Novel hybrid HGSO optimized supervised machine learning approaches to predict the compressive strength of admixed concrete containing fly ash and micro-silica

Chen

2022

Eng. Res. Express

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Thermo-mechanical properties prediction of Ni-reinforced Al2O3 composites using micro-mechanics based representative volume elements

Shahzamanian

Akhtar

Arif

et al. 2022

Sci Rep

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For effective cutting tool inserts that absorb thermal shock at varying temperature gradients, improved thermal conductivity and toughness are required. In addition, parameters such as the coefficient of thermal expansion must be kept within a reasonable range. This work presents a novel material design framework based on a multi-scale modeling approach that proposes nickel (Ni)-reinforced alumina (Al2O3) composites to tailor the mechanical and thermal properties required for ceramic cutting tools by considering numerous composite parameters. The representative volume elements (RVEs) are generated using the DREAM.3D software program and the output is imported into a commercial finite element software ABAQUS. The RVEs which contain multiple Ni particles with varying porosity and volume fractions are used to predict the effective thermal and mechanical properties using the computational homogenization methods under appropriate boundary conditions (BCs). The RVE framework is validated by the sintering of Al2O3-Ni composites in various compositions. The predicted numerical results agree well with the measured thermal and structural properties. The properties predicted by the numerical model are comparable with those obtained using the rules of mixtures and SwiftComp, as well as the Fast Fourier Transform (FFT) based computational homogenization method. The results show that the ABAQUS, SwiftComp and FFT results are fairly close to each other. The effects of porosity and Ni volume fraction on the mechanical and thermal properties are also investigated. It is observed that the mechanical properties and thermal conductivities decrease with the porosity, while the thermal expansion remains unaffected. The proposed integrated modeling and empirical approach could facilitate the development of unique Al2O3-metal composites with the desired thermal and mechanical properties for ceramic cutting inserts.

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Modeling of Cementitious Representative Volume Element with Various Water–Cement Ratios

Shahzamanian

Basirun

2019

J. Multiscale Modelling

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This study uses the finite element method (FEM) to measure the mechanical properties of microstructure-based cementitious representative volume elements (RVEs) with various water–cement ratios (W/Cs) generated by CEMHYD3D. The finite element boundary condition effects that significantly and computationally change the elastic properties are studied and discussed. Various boundary conditions in ABAQUS are applied and compared with the results obtained using the variational asymptotic method for unit cell homogenization (VAMUCH). This comparison is conducted using ANSYS. This study aims to analyze and determine the effect of different boundary conditions in detail on the prediction of the elastic properties of cementitious RVE with various W/Cs and identify the best approach in this regard. Results show that Young’s, shear, and bulk moduli decrease with the increase in W/C and the boundary conditions in ABAQUS influence the outcomes, particularly on bulk modulus and Poisson’s ratio.

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Modeling of Cementitious Representative Volume Element with Additives

Cited by 4 publications

References 59 publications

Novel hybrid HGSO optimized supervised machine learning approaches to predict the compressive strength of admixed concrete containing fly ash and micro-silica

Novel hybrid HGSO optimized supervised machine learning approaches to predict the compressive strength of admixed concrete containing fly ash and micro-silica

Thermo-mechanical properties prediction of Ni-reinforced Al2O3 composites using micro-mechanics based representative volume elements

Modeling of Cementitious Representative Volume Element with Various Water–Cement Ratios

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